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Microb Ecol. 2017 Apr;73(3):658-667. doi: 10.1007/s00248-016-0889-3. Epub 2016 Nov 28.

Reducing the Bottleneck in Discovery of Novel Antibiotics.

Author information

1
Genomic Medicine, J. Craig Venter Institute, La Jolla, CA, USA. marcusjones06@gmail.com.
2
Human Longevity, Inc, San Diego, CA, USA. marcusjones06@gmail.com.
3
Genomic Medicine, J. Craig Venter Institute, La Jolla, CA, USA.
4
Antimicrobial Discovery Center, Department of Biology, Northeastern University, Boston, MA, USA.
5
NovoBiotic Pharmaceuticals, Cambridge, MA, USA.
6
Human Longevity, Inc, San Diego, CA, USA.

Abstract

Most antibiotics were discovered by screening soil actinomycetes, but the efficiency of the discovery platform collapsed in the 1960s. By now, more than 3000 antibiotics have been described and most of the current discovery effort is focused on the rediscovery of known compounds, making the approach impractical. The last marketed broad-spectrum antibiotics discovered were daptomycin, linezolid, and fidaxomicin. The current state of the art in the development of new anti-infectives is a non-existent pipeline in the absence of a discovery platform. This is particularly troubling given the emergence of pan-resistant pathogens. The current practice in dealing with the problem of the background of known compounds is to use chemical dereplication of extracts to assess the relative novelty of a compound it contains. Dereplication typically requires scale-up, extraction, and often fractionation before an accurate mass and structure can be produced by MS analysis in combination with 2D NMR. Here, we describe a transcriptome analysis approach using RNA sequencing (RNASeq) to identify promising novel antimicrobial compounds from microbial extracts. Our pipeline permits identification of antimicrobial compounds that produce distinct transcription profiles using unfractionated cell extracts. This efficient pipeline will eliminate the requirement for purification and structure determination of compounds from extracts and will facilitate high-throughput screen of cell extracts for identification of novel compounds.

KEYWORDS:

Antibiotics; Staphylococcus aureus; Streptomyces; Transcriptome-based dereplication

PMID:
27896376
DOI:
10.1007/s00248-016-0889-3
[Indexed for MEDLINE]

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